A/B testing is a statistical method used to compare two versions of a product, advertisement, or webpage to determine which one performs better. The method involves randomly dividing a target audience into two groups, A and B, and exposing each group to a different version of the product or advertisement. The performance of each version is then measured and compared to determine the one with the better performance.
Statistical significance refers to the likelihood that the results of the A/B test are not due to chance, but are instead a reliable and accurate reflection of the true difference in performance between the two versions.
It is usually determined using statistical tests that take into account the sample size, the size of the difference between the two versions, and the level of variability in the data. If the results are statistically significant, it means that the observed difference is unlikely to have occurred by chance, and can be considered a reliable and accurate result.